CSE Developer Blog

Sequence Intent Classification Using Hierarchical Attention Networks

We analyze how Hierarchical Attention Neural Networks could be helpful with malware detection and classification scenarios, demonstrating the usefulness of this approach for generic sequence intent analysis. The novelty of our approach is in applying techniques that are used to discover structure in a narrative text to data that describes the behavior of executables.

Classifying Leaks Using Cognitive Toolkit

We use Deep Learning to turn a painful and time-consuming leak-detection task for water and oil pipelines into a fast, painless process. Using Python and Fast Fourier Transforms, we turn audio sensor data into images, then use Convolutional Neural Networks to detect and classify pipeline anomalies.

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